Sign In
Personal Schedule
Change Preferences
Search
Browse By Day
Browse By Time
Browse By Person
Browse By Group
Browse By Session Type
Browse By Research Area
Search Tips
AECT 2022 Convention Page
X (Twitter)
While the provision of personalized feedback in higher education is limited due to resource constraints, learning analytics might be beneficial for offering informative feedback when needed by the learner and at scale. Therefore, this quasi-experimental study investigates N = 230 learners’ perceived learning support of five different feedback types learning analytics may offer. Findings indicate that learners perceive the highest learning support from feedback on self-assessment results and in particular when this is enhanced with additional recommendations on how to improve.
Presenter: Clara Schumacher, Humboldt Universität zu Berlin
Presenter: Dirk Ifenthaler, University of Mannheim